Vulnerability-Lookup

CNVD-2017-37855

Vulnerability from cnvd - Published: 2017-12-22

Title

libxls 'xls_appendSST'函数整数溢出漏洞

Description

libxls是一个用于读取Exce（xls）文件的C语言库。 libxls 1.4版本中的'xls_appendSST'函数存在整数溢出漏洞。远程攻击者可借助特制的XLS文件利用该漏洞执行代码（内存破坏）。

Severity

高

Formal description

厂商尚未提供漏洞修复方案，请关注厂商主页更新： http://libxls.sourceforge.net/

Reference

https://nvd.nist.gov/vuln/detail/CVE-2017-12110

Impacted products

Name
libxls libxls 1.4

Show details on source website

JSON

To clipboard

{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2017-12110"
    }
  },
  "description": "libxls\u662f\u4e00\u4e2a\u7528\u4e8e\u8bfb\u53d6Exce\uff08xls\uff09\u6587\u4ef6\u7684C\u8bed\u8a00\u5e93\u3002\r\n\r\nlibxls 1.4\u7248\u672c\u4e2d\u7684\u0027xls_appendSST\u0027\u51fd\u6570\u5b58\u5728\u6574\u6570\u6ea2\u51fa\u6f0f\u6d1e\u3002\u8fdc\u7a0b\u653b\u51fb\u8005\u53ef\u501f\u52a9\u7279\u5236\u7684XLS\u6587\u4ef6\u5229\u7528\u8be5\u6f0f\u6d1e\u6267\u884c\u4ee3\u7801\uff08\u5185\u5b58\u7834\u574f\uff09\u3002",
  "discovererName": "Marcin \u0027Icewall\u0027 Noga of Cisco Talos",
  "formalWay": "\u5382\u5546\u5c1a\u672a\u63d0\u4f9b\u6f0f\u6d1e\u4fee\u590d\u65b9\u6848\uff0c\u8bf7\u5173\u6ce8\u5382\u5546\u4e3b\u9875\u66f4\u65b0\uff1a\r\nhttp://libxls.sourceforge.net/",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2017-37855",
  "openTime": "2017-12-22",
  "products": {
    "product": "libxls libxls 1.4"
  },
  "referenceLink": "https://nvd.nist.gov/vuln/detail/CVE-2017-12110",
  "serverity": "\u9ad8",
  "submitTime": "2017-11-21",
  "title": "libxls \u0027xls_appendSST\u0027\u51fd\u6570\u6574\u6570\u6ea2\u51fa\u6f0f\u6d1e"
}

CVE-2017-12110 (GCVE-0-2017-12110)

Vulnerability from cvelistv5 – Published: 2017-11-20 22:00 – Updated: 2024-09-17 00:11

Summary

An exploitable integer overflow vulnerability exists in the xls_appendSST function of libxls 1.4.A specially crafted XLS file can cause memory corruption resulting in remote code execution.

Severity

8.8 (High)


                        
                          CVSS:3.0/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H

CWE

remote code execution

Assigner

talos mitre root

References

3 references

URL	Tags
https://www.debian.org/security/2018/dsa-4173	vendor-advisoryx_refsource_DEBIAN
https://security.gentoo.org/glsa/202003-64	vendor-advisoryx_refsource_GENTOO
https://www.talosintelligence.com/vulnerability_r…	x_refsource_MISC

Impacted products

1 product

Vendor	Product	Version
libxls	libxls	Affected: 1.4

Date Public

2017-11-20 00:00

Show details on NVD website

JSON

To clipboard

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Sightings

Author	Source	Type	Date	Other

Nomenclature

Seen: The vulnerability was mentioned, discussed, or observed by the user.
Confirmed: The vulnerability has been validated from an analyst's perspective.
Published Proof of Concept: A public proof of concept is available for this vulnerability.
Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
Not confirmed: The user expressed doubt about the validity of the vulnerability.
Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.

Detection rules are retrieved from Rulezet.

The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base model, served locally by ML-Gateway. They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.

Related by attack behaviour

Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.